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You searched for: creator:"Alessandro Lonardo"
[texts]C++ programming language for an abstract massively parallel SIMD architecture - Alessandro Lonardo
The aim of this work is to define and implement an extended C++ language to support the SIMD programming paradigm. The C++ programming language has been extended to express all the potentiality of an abstract SIMD machine consisting of a central Control Processor and a N-dimensional toroidal array of Numeric Processors. Very few extensions have been added to the standard C++ with the goal of minimising the effort for the programmer in learning a new language and to keep very high the performance...
Downloads: 11
[texts]APEnet+: high bandwidth 3D torus direct network for petaflops scale commodity clusters - Roberto Ammendola
We describe herein the APElink+ board, a PCIe interconnect adapter featuring the latest advances in wire speed and interface technology plus hardware support for a RDMA programming model and experimental acceleration of GPU networking; this design allows us to build a low latency, high bandwidth PC cluster, the APEnet+ network, the new generation of our cost-effective, tens-of-thousands-scalable cluster network architecture...
Downloads: 4
[texts]The Distributed Network Processor: a novel off-chip and on-chip interconnection network architecture - Andrea Biagioni
One of the most demanding challenges for the designers of parallel computing architectures is to deliver an efficient network infrastructure providing low latency, high bandwidth communications while preserving scalability. Besides off-chip communications between processors, recent multi-tile (i.e. multi-core) architectures face the challenge for an efficient on-chip interconnection network between processor's tiles...
Downloads: 367
[texts]APEnet+: a 3D toroidal network enabling Petaflops scale Lattice QCD simulations on commodity clusters - Roberto Ammendola
Many scientific computations need multi-node parallelism for matching up both space (memory) and time (speed) ever-increasing requirements. The use of GPUs as accelerators introduces yet another level of complexity for the programmer and may potentially result in large overheads due to the complex memory hierarchy. Additionally, top-notch problems may easily employ more than a Petaflops of sustained computing power, requiring thousands of GPUs orchestrated with some parallel programming model...
Downloads: 1
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